• Energy Research
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• 6. Clean water close
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Abstract In this article, we investigate the intergenerational transmission of sustainable consumption practices. Whereas previous studies have used self-reported attitudes and behaviour, this study uses data on actual energy consumption for space-heating and hot water combined with extensive panel data from Danish administrative registers. The paper shows significant intergenerational correlations between the energy consumption patterns of adults and their mothers, also when controlling for the energy consumption of the mother-in-law, where possible. Furthermore, it shows that the intergenerational correlation is slightly stronger for adults with lower income levels. These results suggest that energy consumption practices are shared and reproduced within the family. Following theories of practice, the intergenerational similarities in energy consumption practices refer to bodily learned practices that are indirectly transmitted and negotiated through family relations. In this way, these findings also contribute to a better understanding of how practical understanding regarding how to perform practices is transmitted within more ordinary aspects of consumption that play a less obvious role in distinction. To ensure more sustainable consumption practices in the future, this paper points to the importance of the role of family relations and the transmission of embodied practices.

Abstract In theory, the control mode of a voltage-sourced converter (VSC) within a multi-terminal HVDC (MTDC) transmission system can be represented by using a droop line characteristic in the active power and DC voltage relationship (Pac–Udc) curve. However, operating the droop control as an extension of the Udc control mode with a steep slope was found to be difficult since it introduces instabilities. This also happens in the extended Pac control with a shallow slope. This paper proposes a droop line tracking (DLT) method for mitigating these issues, i.e. by calculating the new operating point of the converter based on the displacement distance from the droop line. The simulation results show that the proposed method enables the converter to operate in different control modes by simply changing the droop line characteristic. Furthermore, the same concept can be extended to implement the advanced droop control, i.e. represented by a multi-slope droop line characteristic such that the converter can be operated in different control modes depending on the DC system disturbance level. Simulation using a three-terminal HVDC system with an offshore wind farm (OWF) station has been performed to demonstrate the functionality of the proposed method in realizing the advanced droop control mode.

AbstractWith the dramatic developments of renewable and environmental‐friendly electrochemical energy conversion systems, there is an urgent need to fabricate durable and efficient electrocatalysts to address the limitation of high overpotentials exceeding thermodynamic requirements to facilitate practical applications. Recently, tellurium‐based nanomaterials (Te NMs) with unique chemical, electronic, and topological properties, including Te‐derived nanostructures and transition metal tellurides (TMTs), have emerged as one of the most promising electrocatalytic materials. In the absence of comprehensive and guiding reviews, this review comprehensively summarizes the main advances in designing emerging Te NMs for electrocatalysis. First, the engineering strategies and principles of Te NMs to enhance their electrocatalytic activity and stability from the nanostructures to the catalytic atoms are discussed in detail, especially on the chemical/physical/multiplex templating strategies, heteroatom doping, vacancy/defect engineering, phase engineering, and the corresponding mechanisms and structure‐performance correlations. Then, typical applications of Te NMs in electrocatalysis are also discussed in detail. Finally, the existing key issues and main challenges of Te NMs for electrocatalysis are highlighted, and the development trend of Te NMs as electrocatalysts is expounded. This review provides new concepts to guide future directions for developing Te NMs‐based electrocatalysts, thereby promoting their future wide applications in electrochemical energy systems.

Abstract. Lidar systems have the potential of alleviating structural loads on wind turbines by providing a preview of the incoming wind field to the control system. For a collective pitch controller the important quantity of interest is the rotor-effective wind speed (REWS). In this study, we present a model of the coherence between the REWS and its estimate from continuous-wave nacelle-mounted lidar systems. The model uses the spectral tensor definition of the Mann model. Model results were compared to field data gathered from a 2- and 4-beam nacelle lidar mounted on a wind turbine. The comparison shows close agreement for the coherence and the data fits better to the proposed model than to a model based on the Kaimal turbulence model, which underestimates the coherence. Inflow conditions with larger length scales led to a higher coherence between REWS and lidar estimates than inflow turbulence of smaller length scale. When comparing the two lidar systems, it was shown that the 4-beam lidar is able to resolve small turbulent structures with a higher degree of coherence. Further, the advection speed by which the turbulent structures are transported from measurement to rotor plane can be estimated by 10 minute averages of the lidar estimation of REWS. The presented model can be used as a computationally efficient tool to optimize the position of the lidar focus points in order to maximize the coherence.

Large-scale commercialization of drop-in biofuel technologies require a deeper understanding of the molecular structure of biocrude oils and their compatibility with fossil crudes in term of molecu...

Integration of heat and electricity supply improves the overall energy efficiency and system operational flexibility. The renewable powered heat-electricity energy system is a promising way to set up residential energy supply facilities in remote areas beyond the reach of power system infrastructures. However, the volatility of wind and solar energy brings about the risk of supply inadequacy. This article proposes a data-driven robust method to quantify two measures of such a risk in the stand-alone renewable powered heat-electricity energy system. The uncertainty of renewable generation is modeled through a family of ambiguous probability distributions around an empirical one based on the Wasserstein metric; then, the probability of heat and electricity load shedding during a short period and related penalty cost are discussed. Through a polyhedral characterization of renewable power feasible region, the load shedding probability under the Wasserstein ambiguity set comes down to a linear program. With a piecewise linear optimal value function of the penalty cost, its expectation under the worst case distribution in the Wasserstein ambiguity set also gives rise to a linear program. The proposed method requires moderate information on renewable generation and makes full use of available data, whereas sustains computational tractability. The evaluation result is robust against the inaccuracy of renewable power distributions. Case studies demonstrate the effectiveness of the proposed approach.